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Machine Learning in Clinical Neuroimaging - 4th International Workshop, MLCN 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings (Paperback, 1st ed. 2021)
Ahmed Abdulkadir, Seyed Mostafa Kia, Mohamad Habes, Vinod Kumar, Jane Maryam Rondina, …
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R1,651
Discovery Miles 16 510
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 4th
International Workshop on Machine Learning in Clinical
Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction
with MICCAI 2021. The workshop was held virtually due to the
COVID-19 pandemic. The 17 papers presented in this book were
carefully reviewed and selected from 27 submissions. They were
organized in topical sections named: computational anatomy and
brain networks and time series.
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Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Third International Workshop, MLCN 2020, and Second International Workshop, RNO-AI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings (Paperback, 1st ed. 2020)
Seyed Mostafa Kia, Hassan Mohy-ud-Din, Ahmed Abdulkadir, Cher Bass, Mohamad Habes, …
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R1,566
Discovery Miles 15 660
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the Third
International Workshop on Machine Learning in Clinical
Neuroimaging, MLCN 2020, and the Second International Workshop on
Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction
with MICCAI 2020, in Lima, Peru, in October 2020.*For MLCN 2020, 18
papers out of 28 submissions were accepted for publication. The
accepted papers present novel contributions in both developing new
machine learning methods and applications of existing methods to
solve challenging problems in clinical neuroimaging. For RNO-AI
2020, all 8 submissions were accepted for publication. They focus
on addressing the problems of applying machine learning to large
and multi-site clinical neuroimaging datasets. The workshop aimed
to bring together experts in both machine learning and clinical
neuroimaging to discuss and hopefully bridge the existing
challenges of applied machine learning in clinical neuroscience.
*The workshops were held virtually due to the COVID-19 pandemic.
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